Best AI tools for< Compiler Engineer >

BugFree.ai is an AI-powered platform designed to help users practice system design and behavior interviews, similar to Leetcode. The platform offers a range of features to assist users in preparing for technical interviews, including mock interviews, real-time feedback, and personalized study plans. With BugFree.ai, users can improve their problem-solving skills and gain confidence in tackling complex interview questions.

Replexica is an AI-powered i18n compiler for React that is JSON-free and LLM-backed. It is designed for shipping multi-language frontends fast.

Coddy is an AI-powered coding assistant that helps developers write better code faster. It provides real-time feedback, code completion, and error detection, making it the perfect tool for both beginners and experienced developers. Coddy also integrates with popular development tools like Visual Studio Code and GitHub, making it easy to use in your existing workflow.

Replit is a software creation platform that provides an integrated development environment (IDE), artificial intelligence (AI) assistance, and deployment services. It allows users to build, test, and deploy software projects directly from their browser, without the need for local setup or configuration. Replit offers real-time collaboration, code generation, debugging, and autocompletion features powered by AI. It supports multiple programming languages and frameworks, making it suitable for a wide range of development projects.

illbeback.ai is the #1 site for AI jobs around the world. It provides a platform for both job seekers and employers to connect in the field of Artificial Intelligence. The website features a wide range of AI job listings from top companies, offering opportunities for professionals in the AI industry to advance their careers. With a user-friendly interface, illbeback.ai simplifies the job search process for AI enthusiasts and provides valuable resources for companies looking to hire AI talent.

Anycores is an AI tool designed to optimize the performance of deep neural networks and reduce the cost of running AI models in the cloud. It offers a platform that provides automated solutions for tuning and inference consultation, optimized networks zoo, and platform for reducing AI model cost. Anycores focuses on faster execution, reducing inference time over 10x times, and footprint reduction during model deployment. It is device agnostic, supporting Nvidia, AMD GPUs, Intel, ARM, AMD CPUs, servers, and edge devices. The tool aims to provide highly optimized, low footprint networks tailored to specific deployment scenarios.

Twig AI is an AI tool designed for Customer Experience, offering an AI assistant that resolves customer issues instantly, supporting both users and support agents 24/7. It provides features like converting user requests into API calls, instant responses for user questions, and factual answers cited with trustworthy sources. Twig simplifies data retrieval from external sources, offers personalization options, and includes a built-in knowledge base. The tool aims to drive agent productivity, provide insights to monitor customer experience, and offers various application interfaces for different user roles.

ONNX is an open standard for machine learning interoperability, providing a common format to represent machine learning models. It defines a set of operators and a file format for AI developers to use models across various frameworks, tools, runtimes, and compilers. ONNX promotes interoperability, hardware access, and community engagement.

Visual Studio is an integrated development environment (IDE) and code editor designed for software developers and teams. It offers a comprehensive set of tools and features to enhance every stage of software development, including code editing, debugging, building, and publishing applications. Visual Studio also includes compilers, code completion tools, graphical designers, and AI-powered coding assistance through GitHub Copilot integration.

Narada is an AI application designed for busy professionals to streamline their work processes. It leverages cutting-edge AI technology to automate tasks, connect favorite apps, and enhance productivity through intelligent automation. Narada's LLM Compiler routes text and voice commands to the right tools in real time, offering seamless app integration and time-saving features.

GetSelected.ai is a personal AI-powered interviewer platform that helps users enhance their interview skills through AI technology. The platform offers features such as mock interviews, personalized feedback, job position customization, AI-driven quizzes, resume optimization, and code compiler for IT roles. Users can practice interview scenarios, improve communication skills, and prepare for recruitment processes with the help of AI tools. GetSelected.ai aims to provide a comprehensive and customizable experience to meet unique career goals and stand out in the competitive job market.

PseudoEditor is an online pseudocode editor that offers a free, fast, and dynamic platform for writing and testing pseudocode. It includes features like syntax highlighting, code saving, and error highlighting to enhance the coding experience. With the ability to save code and resume work from any device, PseudoEditor aims to streamline the process of writing pseudocode and creating algorithms. The platform is supported by ads, ensuring that users can access the editor for free.

Roadmapped.ai is an AI-powered platform designed to help users learn various topics efficiently and quickly. By providing a structured roadmap generated in seconds, the platform eliminates the need to navigate through scattered online resources aimlessly. Users can input a topic they want to learn, and the AI will generate a personalized roadmap with curated resources. The platform also offers features like AI-powered YouTube search, saving roadmaps, priority support, and access to a private Discord community.

SoraPrompt is an AI model that can create realistic and imaginative scenes from text instructions. It is the latest text-to-video technology from the OpenAI development team. Users can compile text prompts to generate video query summaries for efficient content analysis. SoraPrompt also allows users to share their interests and ideas with others.

Rargus is a generative AI tool that specializes in turning customer feedback into actionable insights for businesses. By collecting feedback from various channels and utilizing custom AI analysis, Rargus helps businesses understand customer needs and improve product development. The tool enables users to compile and analyze feedback efficiently, leading to data-driven decision-making and successful product launches. Rargus also offers solutions for consumer insights, product management, and product marketing, helping businesses enhance customer satisfaction and drive growth.

AI Document Creator is an innovative tool that leverages artificial intelligence to assist users in generating various types of documents efficiently. The application utilizes advanced algorithms to analyze input data and create well-structured documents tailored to the user's needs. With AI Document Creator, users can save time and effort in document creation, ensuring accuracy and consistency in their outputs. The tool is user-friendly and accessible, making it suitable for individuals and businesses seeking to streamline their document creation process.

Dokkio is an AI-powered platform that helps users find, organize, and understand all of their online files. By leveraging AI technology, Dokkio enables users to work with their cloud files efficiently and collaboratively. The platform offers tools for managing multiple activities, finding documents and files, compiling research materials, and organizing a content library. Dokkio aims to streamline the process of accessing and utilizing online content, regardless of where it is stored.

Bandofacile is an AI-powered platform designed to simplify the process of accessing and applying for financial grants and opportunities for both companies and consultants. By leveraging artificial intelligence, Bandofacile streamlines the process of finding suitable grants, answering application questions, and receiving completed documentation. The platform offers various services tailored to the specific needs of users, ensuring a stress-free approach to participating in grant opportunities.

Smarty is an AI-powered productivity tool that acts as an execution engine for businesses. It combines AI technology with human experts to help users manage tasks, events, scheduling, and productivity. Smarty offers features like natural-language-based console, unified view of tasks and calendar, automatic prioritization, brain dumping, automation shortcuts, and personalized interactions. It helps users work smarter, stay organized, and save time by streamlining workflows and enhancing productivity. Smarty is designed to be a versatile task organizer app suitable for professionals looking to optimize daily planning and task management.

Extractify.co is a website that offers a variety of tools and services for extracting information from different sources. The platform provides users with the ability to extract data from websites, documents, and other sources in a quick and efficient manner. With a user-friendly interface, Extractify.co aims to simplify the process of data extraction for individuals and businesses alike. Whether you need to extract text, images, or other types of data, Extractify.co has the tools to help you get the job done. The platform is designed to be intuitive and easy to use, making it accessible to users of all skill levels.

The ByteIR Project is a ByteDance model compilation solution. ByteIR includes compiler, runtime, and frontends, and provides an end-to-end model compilation solution. Although all ByteIR components (compiler/runtime/frontends) are together to provide an end-to-end solution, and all under the same umbrella of this repository, each component technically can perform independently. The name, ByteIR, comes from a legacy purpose internally. The ByteIR project is NOT an IR spec definition project. Instead, in most scenarios, ByteIR directly uses several upstream MLIR dialects and Google Mhlo. Most of ByteIR compiler passes are compatible with the selected upstream MLIR dialects and Google Mhlo.

Aiwnios is a HolyC Compiler/Runtime designed for 64-bit ARM, RISCV, and x86 machines, including Apple M1 Macs, with plans for supporting other architectures in the future. The project is currently a work in progress, with regular updates and improvements planned. Aiwnios includes a sockets API (currently tested on FreeBSD) and a HolyC assembler accessible through AARCH64. The heart of Aiwnios lies in `arm_backend.c`, where the compiler is located, and a powerful AARCH64 assembler in `arm64_asm.c`. The compiler uses reverse Polish notation and statements are reversed. The developer manual is intended for developers working on the C side, providing detailed explanations of the source code.

This repository extends the LLVM framework to generate code for use with AMD/Xilinx AI Engine processors. AI Engine processors are in-order, exposed-pipeline VLIW processors focused on application acceleration for AI, Machine Learning, and DSP applications. The repository adds LLVM support for specific features like non-power of 2 pointers, operand latencies, resource conflicts, negative operand latencies, slot assignment, relocations, code alignment restrictions, and register allocation. It includes support for Clang, LLD, binutils, Compiler-RT, and LLVM-LIBC.

This repository contains an early-phase IREE compiler and runtime plugin for interfacing the AMD AIE accelerator to IREE. It provides architectural overview, developer setup instructions, building guidelines, and runtime driver setup details. The repository focuses on enabling the integration of the AMD AIE accelerator with IREE, offering developers the tools and resources needed to build and run applications leveraging this technology.

Husky is a research-focused programming language designed for next-generation computing. It aims to provide a powerful and ergonomic development experience for various tasks, including system level programming, web/native frontend development, parser/compiler tasks, game development, formal verification, machine learning, and more. With a strong type system and support for human-in-the-loop programming, Husky enables users to tackle complex tasks such as explainable image classification, natural language processing, and reinforcement learning. The language prioritizes debugging, visualization, and human-computer interaction, offering agile compilation and evaluation, multiparadigm support, and a commitment to a good ecosystem.

Llama3.java is a practical Llama 3 inference tool implemented in a single Java file. It serves as the successor of llama2.java and is designed for testing and tuning compiler optimizations and features on the JVM, especially for the Graal compiler. The tool features a GGUF format parser, Llama 3 tokenizer, Grouped-Query Attention inference, support for Q8_0 and Q4_0 quantizations, fast matrix-vector multiplication routines using Java's Vector API, and a simple CLI with 'chat' and 'instruct' modes. Users can download quantized .gguf files from huggingface.co for model usage and can also manually quantize to pure 'Q4_0'. The tool requires Java 21+ and supports running from source or building a JAR file for execution. Performance benchmarks show varying tokens/s rates for different models and implementations on different hardware setups.

This repository contains tools and libraries for building AIR platforms, runtimes and compilers.

AILZ80ASM is a Z80 assembler that runs in a .NET 8 environment written in C#. It can be used to assemble Z80 assembly code and generate output files in various formats. The tool supports various command-line options for customization and provides features like macros, conditional assembly, and error checking. AILZ80ASM offers good performance metrics with fast assembly times and efficient output file sizes. It also includes support for handling different file encodings and provides a range of built-in functions for working with labels, expressions, and data types.

Bodo is a high-performance Python compute engine designed for large-scale data processing and AI workloads. It utilizes an auto-parallelizing just-in-time compiler to optimize Python programs, making them 20x to 240x faster compared to alternatives. Bodo seamlessly integrates with native Python APIs like Pandas and NumPy, eliminates runtime overheads using MPI for distributed execution, and provides exceptional performance and scalability for data workloads. It is easy to use, interoperable with the Python ecosystem, and integrates with modern data platforms like Apache Iceberg and Snowflake. Bodo focuses on data-intensive and computationally heavy workloads in data engineering, data science, and AI/ML, offering automatic optimization and parallelization, linear scalability, advanced I/O support, and a high-performance SQL engine.

Kumo search is an end-to-end search engine framework that supports full-text search, inverted index, forward index, sorting, caching, hierarchical indexing, intervention system, feature collection, offline computation, storage system, and more. It runs on the EA (Elastic automic infrastructure architecture) platform, enabling engineering automation, service governance, real-time data, service degradation, and disaster recovery across multiple data centers and clusters. The framework aims to provide a ready-to-use search engine framework to help users quickly build their own search engines. Users can write business logic in Python using the AOT compiler in the project, which generates C++ code and binary dynamic libraries for rapid iteration of the search engine.

Yalm (Yet Another Language Model) is an LLM inference implementation in C++/CUDA, emphasizing performance engineering, documentation, scientific optimizations, and readability. It is not for production use and has been tested on Mistral-v0.2 and Llama-3.2. Requires C++20-compatible compiler, CUDA toolkit, and LLM safetensor weights in huggingface format converted to .yalm file.

BAML is a config file format for declaring LLM functions that you can then use in TypeScript or Python. With BAML you can Classify or Extract any structured data using Anthropic, OpenAI or local models (using Ollama) ## Resources  [Discord Community](https://discord.gg/boundaryml)  [Follow us on Twitter](https://twitter.com/boundaryml) * Discord Office Hours - Come ask us anything! We hold office hours most days (9am - 12pm PST). * Documentation - Learn BAML * Documentation - BAML Syntax Reference * Documentation - Prompt engineering tips * Boundary Studio - Observability and more #### Starter projects * BAML + NextJS 14 * BAML + FastAPI + Streaming ## Motivation Calling LLMs in your code is frustrating: * your code uses types everywhere: classes, enums, and arrays * but LLMs speak English, not types BAML makes calling LLMs easy by taking a type-first approach that lives fully in your codebase: 1. Define what your LLM output type is in a .baml file, with rich syntax to describe any field (even enum values) 2. Declare your prompt in the .baml config using those types 3. Add additional LLM config like retries or redundancy 4. Transpile the .baml files to a callable Python or TS function with a type-safe interface. (VSCode extension does this for you automatically). We were inspired by similar patterns for type safety: protobuf and OpenAPI for RPCs, Prisma and SQLAlchemy for databases. BAML guarantees type safety for LLMs and comes with tools to give you a great developer experience:  Jump to BAML code or how Flexible Parsing works without additional LLM calls. | BAML Tooling | Capabilities | | ----------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | BAML Compiler install | Transpiles BAML code to a native Python / Typescript library (you only need it for development, never for releases) Works on Mac, Windows, Linux  | | VSCode Extension install | Syntax highlighting for BAML files Real-time prompt preview Testing UI | | Boundary Studio open (not open source) | Type-safe observability Labeling |

This repository is a collection of tools and resources for deep learning infrastructure, covering programming languages, algorithms, acceleration techniques, and engineering aspects. It provides information on various online tools for chip architecture, CPU and GPU benchmarks, and code analysis. Additionally, it includes content on AI compilers, deep learning models, high-performance computing, Docker and Kubernetes tutorials, Protobuf and gRPC guides, and programming languages such as C++, Python, and Shell. The repository aims to bridge the gap between algorithm understanding and engineering implementation in the fields of AI and deep learning.

This repository contains an MLIR-based toolchain for AI Engine-enabled devices, such as AMD Ryzen™ AI and Versal™. This repository can be used to generate low-level configurations for the AI Engine portion of these devices. AI Engines are organized as a spatial array of tiles, where each tile contains AI Engine cores and/or memories. The spatial array is connected by stream switches that can be configured to route data between AI Engine tiles scheduled by their programmable Data Movement Accelerators (DMAs). This repository contains MLIR representations, with multiple levels of abstraction, to target AI Engine devices. This enables compilers and developers to program AI Engine cores, as well as describe data movements and array connectivity. A Python API is made available as a convenient interface for generating MLIR design descriptions. Backend code generation is also included, targeting the aie-rt library. This toolchain uses the AI Engine compiler tool which is part of the AMD Vitis™ software installation: these tools require a free license for use from the Product Licensing Site.

LLM-PLSE-paper is a repository focused on the applications of Large Language Models (LLMs) in Programming Language and Software Engineering (PL/SE) domains. It covers a wide range of topics including bug detection, specification inference and verification, code generation, fuzzing and testing, code model and reasoning, code understanding, IDE technologies, prompting for reasoning tasks, and agent/tool usage and planning. The repository provides a comprehensive collection of research papers, benchmarks, empirical studies, and frameworks related to the capabilities of LLMs in various PL/SE tasks.

Awesome Mobile LLMs is a curated list of Large Language Models (LLMs) and related studies focused on mobile and embedded hardware. The repository includes information on various LLM models, deployment frameworks, benchmarking efforts, applications, multimodal LLMs, surveys on efficient LLMs, training LLMs on device, mobile-related use-cases, industry announcements, and related repositories. It aims to be a valuable resource for researchers, engineers, and practitioners interested in mobile LLMs.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

This repository provides a comprehensive guide to large language models (LLMs), covering various aspects such as training, fine-tuning, compression, and applications. It includes detailed tutorials, code examples, and explanations of key concepts and techniques. The repository is maintained by Liguo Dong, an AI researcher and engineer with expertise in LLM research and development.

hongbomiao.com is a personal research and development (R&D) lab that facilitates the sharing of knowledge. The repository covers a wide range of topics including web development, mobile development, desktop applications, API servers, cloud native technologies, data processing, machine learning, computer vision, embedded systems, simulation, database management, data cleaning, data orchestration, testing, ops, authentication, authorization, security, system tools, reverse engineering, Ethereum, hardware, network, guidelines, design, bots, and more. It provides detailed information on various tools, frameworks, libraries, and platforms used in these domains.

Expert in compiler techniques and frameworks.

A Zig Language Specialist

I'm a tutor for JavaScript and Melange, a compiler for OCaml that targets JavaScript.

Cricket AI with a secret recipe for cricket info and odds.

OCamlは至高の言語

Compile instructions from the web and github for bioinformatics applications. Receive line-by-line instructions and commands to get started

FlutterCraft is an AI-powered assistant that streamlines Flutter app development. It interprets user-provided descriptions to generate and compile Flutter app code, providing ready-to-install APK and iOS files. Ideal for rapid prototyping, FlutterCraft makes app development accessible and efficient.

By combining the expertise of top career coaches with advanced AI, our GPT helps you excel in interviews across various job functions and levels. We've also compiled the most practical tips for you | We value your experience, please contact [email protected] if you need support ❤️!

Expert in Raspberry Pi kernels and Python blockchain

Formal and professional Linux Kernel Expert, adept in technical jargon.

Write ReScript code. Trained with versions 10 & 11. Documentation github.com/guillempuche/gpt-rescript

中文代码编译专家

I compile and enrich precise company and professional profiles. Simply provide any name, email address, or company and I'll generate a complete profile.

Compiles technical feedback for recruiters

I compile neat, structured meeting minutes.

Natural remedies for over 220 Ailments Compiled from 5 Years of Extensive Research.

Crafts full coloring books with a cover and compiled into a downloadable document.

Get your daily horoscope summary, categorized and compiled from various online sources. For entertainment purposes only.

Friendly and normal LaTeX coding assistant.